Abstract
Unmanned aerial vehicles may collide with obstacles, such as trees or other unmanned aerial vehicles, while flying. A waypoint-based flight path is an approach to avoid such obstacles. To specify waypoints for the safe flight of unmanned aerial vehicles, it is necessary to define a flight path in advance by analyzing the flight records of unmanned aerial vehicles and thereby designate the waypoints automatically. However, there is a problem in that pilots tend to make errors in controlling unmanned aerial vehicles and collecting flight records. This article proposes a method to generate candidate waypoints for a flight path by removing such unintended flight records. In this method, images representing the positions in the collected flight records are generated. The candidate waypoints are generated as positions corresponding to the overlapping pixels of the images generated via image accumulation based on the flight records and the ones generated by accumulating the images reconstructed using an Autoencoder. The unmanned aerial vehicles can be set the waypoints for an autonomous flight using the candidate waypoints. An experiment was conducted in a university to generate candidate waypoints for road monitoring. The results obtained using the proposed method and K-means algorithm were compared. The candidate waypoints generated using the proposed method were reduced by 84.21% compared to those generated using the K-means algorithm.
Highlights
Unmanned aerial vehicles (UAVs)[1] autonomously fly using onboard cameras and perform monitoring functions such as traffic regulation using onboard cameras.[2,3,4,5]
This article proposed a method to generate candidate waypoints based on flight records
To generate the candidate waypoints, the collected flight records were generated as images, which were inputted to an Autoencoder
Summary
Unmanned aerial vehicles (UAVs)[1] autonomously fly using onboard cameras and perform monitoring functions such as traffic regulation using onboard cameras.[2,3,4,5] A pilot can control each UAV by watching UAV camera screens and considering UAV positions.[6,7] it is difficult for a single pilot to control UAVs concurrently. It is necessary to remove such unintended positions due to pilot error from the generated flight records. This article proposes a method of generating candidate waypoints for UAVs, wherein the unintended flight data due to pilot error are removed using Autoencoder. Based on the maximum position, minimum position, and error range of the sensor in measuring the position, images representing the positions included in the flight record are generated. It is possible to specify the waypoints for UAVs based on the flight paths without reflecting any unintended flight records due to pilot error. Section ‘‘Autoencoder-based candidate waypoint generation method using images representing flight records’’ details a candidate waypoints generation method for an autonomous flight using the Autoencoder. Section ‘‘Conclusion’’ presents the conclusions drawn from this study
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